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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 11 | Copyright
Geosci. Model Dev., 11, 4399-4416, 2018
https://doi.org/10.5194/gmd-11-4399-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model evaluation paper 02 Nov 2018

Model evaluation paper | 02 Nov 2018

Carbon–nitrogen coupling under three schemes of model representation: a traceability analysis

Zhenggang Du1, Ensheng Weng2, Lifen Jiang3, Yiqi Luo3,4, Jianyang Xia1,5, and Xuhui Zhou1,6 Zhenggang Du et al.
  • 1Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200062, China
  • 2Center for Climate Systems Research, Columbia University, NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025, USA
  • 3Center for Ecosystem Science and Society, Northern Arizona University, AZ, USA
  • 4Department for Earth System Science, Tsinghua University, Beijing 100084, China
  • 5Forest Ecosystem Research and Observation Station in Putuo Island, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200062, China
  • 6Shanghai Institute of Pollution Control and Ecological Security, 1515 North Zhongshan Rd, Shanghai 200437, China

Abstract. The interaction between terrestrial carbon (C) and nitrogen (N) cycles has been incorporated into more and more land surface models. However, the scheme of C–N coupling differs greatly among models, and how these diverse representations of C–N interactions will affect C-cycle modeling remains unclear. In this study, we explored how the simulated ecosystem C storage capacity in the terrestrial ecosystem (TECO) model varied with three different commonly used schemes of C–N coupling. The three schemes (SM1, SM2, and SM3) have been used in three different coupled C–N models (i.e., TECO-CN, CLM 4.5, and O-CN, respectively). They differ mainly in the stoichiometry of C and N in vegetation and soils, plant N uptake strategies, downregulation of photosynthesis, and the pathways of N import. We incorporated the three C–N coupling schemes into the C-only version of the TECO model and evaluated their impacts on the C cycle with a traceability framework. Our results showed that all three of the C–N schemes caused significant reductions in steady-state C storage capacity compared with the C-only version with magnitudes of −23%, −30%, and −54% for SM1, SM2, and SM3, respectively. This reduced C storage capacity was mainly derived from the combined effects of decreases in net primary productivity (NPP; −29%, −15%, and −45%) and changes in mean C residence time (MRT; 9%, −17%, and −17%) for SM1, SM2, and SM3, respectively. The differences in NPP are mainly attributed to the different assumptions on plant N uptake, plant tissue C : N ratio, downregulation of photosynthesis, and biological N fixation. In comparison, the alternative representations of the plant vs. microbe competition strategy and the plant N uptake, combined with the flexible C : N ratio in vegetation and soils, led to a notable spread in MRT. These results highlight the fact that the diverse assumptions on N processes represented by different C–N coupled models could cause additional uncertainty for land surface models. Understanding their difference can help us improve the capability of models to predict future biogeochemical cycles of terrestrial ecosystems.

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In this study, based on a traceability analysis technique, we evaluated alternative representations of C–N interactions and their impacts on the C cycle using the TECO model framework. Our results showed that different representations of C–N coupling processes lead to divergent effects on plant production, C residence time, and thus the ecosystem C storage capacity. Identifying those effects can help us to improve the N limitation assumptions employed in terrestrial ecosystem models.
In this study, based on a traceability analysis technique, we evaluated alternative...
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